Position: AI Safety Requires Effective Controllability
The paper discusses the importance of controllability in AI safety, arguing that alignment alone is insufficient. It emphasizes the need for AI systems to be reliably interruptible and manageable in real-time scenarios. The authors propose a new framework and benchmark to evaluate controllability in high-risk environments.
- ▪AI safety has traditionally focused on alignment with human preferences.
- ▪The authors argue that controllability should be a primary objective for AI systems.
- ▪They introduce a benchmark called controlbench to assess controllability failures.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.27117 |
| Publication time | Wed, 27 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-27T04:07:56.398Z |
| Last seen | 2026-05-27T04:07:56.398Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | qsRCXSsK5W_T |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.27117 (cs) [Submitted on 26 May 2026] Title:Position: AI Safety Requires Effective Controllability Authors:Yige Li, Yunhao Feng, Jun Sun View a PDF of the paper titled Position: AI Safety Requires Effective Controllability, by Yige Li and 2 other authors View PDF HTML (experimental) Abstract:AI safety is still largely framed as alignment: training models to follow human preferences, safety policies, and normative constraints. That framing has improved the behavior of modern language models, but aligned behavior does not by itself guarantee that a deployed agent can be stopped, overridden, or constrained once it operates in open-ended, interactive, and tool-using environments.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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